Storage Engineer

Our client, a high-performance technology-driven trading firm, is seeking a Storage Infrastructure Engineer to help evolve and scale the platforms that support large-scale data storage, processing, and distribution across the business. This role is ideal for an engineer who enjoys working deep within Linux environments, optimizing system performance, and building highly reliable infrastructure from the ground up.

As data volumes continue to expand, you will play a critical role in designing, automating, and maintaining the storage ecosystem that supports latency-sensitive workloads and data-intensive applications.

Responsibilities

• Architect, deploy, and maintain large-scale storage platforms, including distributed storage systems, object storage solutions, and data lake environments
• Optimize Linux systems for storage efficiency, throughput, and overall performance
• Develop and enhance infrastructure automation using tools such as Ansible, Puppet, or similar frameworks
• Implement monitoring, alerting, and observability solutions to improve platform reliability and operational visibility
• Collaborate with software and platform engineering teams to deliver scalable data infrastructure solutions
• Support and enhance data streaming and messaging technologies, including Kafka-based environments
• Contribute to containerized infrastructure initiatives leveraging Kubernetes and related technologies

Storage Software, Data Storage, Linux Operating System, Software Engineering, Performance Tuning/Optimization, Storage Software, Ecosystems, Data Lake, Distributed Computing, Automation, * 5+ years of experience in infrastructure, systems, or platform engineering with a focus on storage technologies

• Strong expertise in Linux administration, troubleshooting, and performance tuning
• Hands-on experience with infrastructure-as-code and configuration management tools such as Ansible or Puppet
• Knowledge of distributed storage platforms, object storage technologies, and enterprise storage environments
• Experience supporting large-scale data platforms and big data ecosystems
• Programming or scripting experience with Python, Java, or similar languages
• Familiarity with modern observability and monitoring solutions, including Prometheus
• Experience working within highly automated engineering environments and leveraging AI-assisted development tools
• Exposure to container orchestration platforms such as Kubernetes

Preferred Background

• Experience supporting large-scale data pipelines, analytics infrastructure, or real-time data environments
• Familiarity with high-performance computing, low-latency infrastructure, or financial technology environments
• Understanding of distributed systems architecture and scalability best practices